The ever increasing availability of high throughput computer network connections has enabled computer processing capability to be distributed among many different computing devices that can be spread out across a variety of physical locations. For example, data centers, housing hundreds or thousands of computing devices, are becoming more commonplace, both among entities that seek to utilize for themselves the processing capabilities supported by such datacenters, and by entities that seek to sell such processing capabilities to others. Irrespective of the manner in which data centers are monetized, each data center, and the computing devices and associated hardware contained therein, can represent a substantial financial investment. More specifically, much of the hardware that comprises a data center, especially the computational hardware, can, not only, require an initial outlay of capital to purchase such hardware, but can also represent a depreciating asset whose value decreases over time.
Consequently, it can be financially beneficial to track hardware to ensure that it is being utilized in an efficient manner and to ensure that operational parameters, such as voltage, current, temperature and other like parameters, are being met. Unfortunately, tracking and managing a myriad of hardware across diverse geographic locations can be difficult to implement. For example, a single data center can comprise thousands of computing devices and associated hardware that can need to be individually tracked and managed. Many organizations, however, can manage multiple data centers that can be spread across diverse geographic locations, exponentially increasing the amount of hardware to be maintained and managed.
Traditional mechanisms for managing hardware, especially large volumes of physically distributed hardware, comprise the utilization of a myriad of complex communicational protocols. Such mechanisms can be inefficient and prone to error.